{"title":"Longterm Decision Making Under the Threat of Earthquakes","authors":"Carmen Camacho, Yu Sun","doi":"10.2139/ssrn.3298413","DOIUrl":null,"url":null,"abstract":"Under the threat of earthquakes, long-term policy makers need tools to decide optimally on the economic trajectories that maximize the society welfare. Tools should be flexible and account for the consequences of earthquakes, incorporating the best estimate of their frequency and intensity. In this regard, we propose in this paper a modeling strategy that combines optimal control techniques and Bayesian learning: after an earthquake occurs, policy makers can improve their knowledge and adjust policies optimally. Two numerical examples illustrate the advantages of our modelling strategy along different dimensions. While Japan symbolizes the policy maker who has learned from earthquakes protecting the economy accordingly; Italy helps us illustrate the importance of prevention capital.","PeriodicalId":210701,"journal":{"name":"Decision-Making in Public Policy & the Social Good eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision-Making in Public Policy & the Social Good eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3298413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Under the threat of earthquakes, long-term policy makers need tools to decide optimally on the economic trajectories that maximize the society welfare. Tools should be flexible and account for the consequences of earthquakes, incorporating the best estimate of their frequency and intensity. In this regard, we propose in this paper a modeling strategy that combines optimal control techniques and Bayesian learning: after an earthquake occurs, policy makers can improve their knowledge and adjust policies optimally. Two numerical examples illustrate the advantages of our modelling strategy along different dimensions. While Japan symbolizes the policy maker who has learned from earthquakes protecting the economy accordingly; Italy helps us illustrate the importance of prevention capital.